A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma
Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleo...
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Veröffentlicht in: | Blood 2021-08, Vol.138 (6), p.452-463 |
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creator | Tian, Xiao-Peng Ma, Shu-Yun Young, Ken H. Ong, Choon Kiat Liu, Yan-Hui Li, Zhi-Hua Zhai, Qiong-Li Huang, Hui-Qiang Lin, Tong-Yu Li, Zhi-Ming Xia, Zhong-Jun Zhong, Li-Ye Rao, Hui-Lan Li, Mei Cai, Jun Zhang, Yu-Chen Zhang, Fen Su, Ning Li, Peng-Fei Zhu, Feng Xu-Monette, Zijun Y. Wong, Esther Kam Yin Ha, Jeslin Chian Hung Khoo, Lay Poh Ai, Le Cheng, Run-Fen Lim, Jing Quan de Mel, Sanjay Ng, Siok-Bian Lim, Soon Thye Cai, Qing-Qing |
description | Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP–based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP–based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P < .001). The 7-SNP–based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP–based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP–based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.
•The 7-SNP-based classifier is an effective and reliable predictor of survival for patients with ENKTL.•The 7-SNP-based signature can be used as a supplement to current risk indicators, aiding clinical decision making.
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doi_str_mv | 10.1182/blood.2020010637 |
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•The 7-SNP-based classifier is an effective and reliable predictor of survival for patients with ENKTL.•The 7-SNP-based signature can be used as a supplement to current risk indicators, aiding clinical decision making.
[Display omitted]</description><identifier>ISSN: 0006-4971</identifier><identifier>EISSN: 1528-0020</identifier><identifier>DOI: 10.1182/blood.2020010637</identifier><identifier>PMID: 33728448</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><ispartof>Blood, 2021-08, Vol.138 (6), p.452-463</ispartof><rights>2021 American Society of Hematology</rights><rights>Copyright © 2021 American Society of Hematology.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-a46c238262257c592d6495e8d5a3899c82cd078f12f23873ec47f0237d7216593</citedby><cites>FETCH-LOGICAL-c392t-a46c238262257c592d6495e8d5a3899c82cd078f12f23873ec47f0237d7216593</cites><orcidid>0000-0002-9356-2154 ; 0000-0002-0366-5505 ; 0000-0002-5755-8932 ; 0000-0001-5447-3282 ; 0000-0003-3732-8707 ; 0000-0001-6402-4288 ; 0000-0001-6051-6410</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33728448$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tian, Xiao-Peng</creatorcontrib><creatorcontrib>Ma, Shu-Yun</creatorcontrib><creatorcontrib>Young, Ken H.</creatorcontrib><creatorcontrib>Ong, Choon Kiat</creatorcontrib><creatorcontrib>Liu, Yan-Hui</creatorcontrib><creatorcontrib>Li, Zhi-Hua</creatorcontrib><creatorcontrib>Zhai, Qiong-Li</creatorcontrib><creatorcontrib>Huang, Hui-Qiang</creatorcontrib><creatorcontrib>Lin, Tong-Yu</creatorcontrib><creatorcontrib>Li, Zhi-Ming</creatorcontrib><creatorcontrib>Xia, Zhong-Jun</creatorcontrib><creatorcontrib>Zhong, Li-Ye</creatorcontrib><creatorcontrib>Rao, Hui-Lan</creatorcontrib><creatorcontrib>Li, Mei</creatorcontrib><creatorcontrib>Cai, Jun</creatorcontrib><creatorcontrib>Zhang, Yu-Chen</creatorcontrib><creatorcontrib>Zhang, Fen</creatorcontrib><creatorcontrib>Su, Ning</creatorcontrib><creatorcontrib>Li, Peng-Fei</creatorcontrib><creatorcontrib>Zhu, Feng</creatorcontrib><creatorcontrib>Xu-Monette, Zijun Y.</creatorcontrib><creatorcontrib>Wong, Esther Kam Yin</creatorcontrib><creatorcontrib>Ha, Jeslin Chian Hung</creatorcontrib><creatorcontrib>Khoo, Lay Poh</creatorcontrib><creatorcontrib>Ai, Le</creatorcontrib><creatorcontrib>Cheng, Run-Fen</creatorcontrib><creatorcontrib>Lim, Jing Quan</creatorcontrib><creatorcontrib>de Mel, Sanjay</creatorcontrib><creatorcontrib>Ng, Siok-Bian</creatorcontrib><creatorcontrib>Lim, Soon Thye</creatorcontrib><creatorcontrib>Cai, Qing-Qing</creatorcontrib><title>A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma</title><title>Blood</title><addtitle>Blood</addtitle><description>Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP–based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP–based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P < .001). The 7-SNP–based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP–based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP–based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.
•The 7-SNP-based classifier is an effective and reliable predictor of survival for patients with ENKTL.•The 7-SNP-based signature can be used as a supplement to current risk indicators, aiding clinical decision making.
[Display omitted]</description><issn>0006-4971</issn><issn>1528-0020</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kEtPxSAQRonR6PWxd2W6dFOFoS3UnTG-EhM3uiYIU0VpqdAa778XvT5WriaZnO_LzCFkn9EjxiQcP_gQ7BFQoJTRhos1smA1yJLmzTpZUEqbsmoF2yLbKT1nqOJQb5ItzgXIqpIL0p8WJvRjSG7CIrnh0WM5zMZjmJzFYgx-2Yc4PrnUF2NE68zkwpDJx0FPc8SiC7HA9ynqIVjti69tni_Oe4zHd6VB74tcMj6FXu-SjU77hHvfc4fcX5zfnV2VN7eX12enN6XhLUylrhoDXEIDUAtTt2Cbqq1R2lpz2bZGgrFUyI5BlzHB0VSio8CFFcCauuU75HDVO8bwOmOaVO_S5yV6wDAnBTUFoJwzkVG6Qk0MKUXs1Bhdr-NSMao-JasvyepPco4cfLfPDz3a38CP1QycrADMP745jCoZh4PJ-iKaSdng_m__AEgsjTA</recordid><startdate>20210812</startdate><enddate>20210812</enddate><creator>Tian, Xiao-Peng</creator><creator>Ma, Shu-Yun</creator><creator>Young, Ken H.</creator><creator>Ong, Choon Kiat</creator><creator>Liu, Yan-Hui</creator><creator>Li, Zhi-Hua</creator><creator>Zhai, Qiong-Li</creator><creator>Huang, Hui-Qiang</creator><creator>Lin, Tong-Yu</creator><creator>Li, Zhi-Ming</creator><creator>Xia, Zhong-Jun</creator><creator>Zhong, Li-Ye</creator><creator>Rao, Hui-Lan</creator><creator>Li, Mei</creator><creator>Cai, Jun</creator><creator>Zhang, Yu-Chen</creator><creator>Zhang, Fen</creator><creator>Su, Ning</creator><creator>Li, Peng-Fei</creator><creator>Zhu, Feng</creator><creator>Xu-Monette, Zijun Y.</creator><creator>Wong, Esther Kam Yin</creator><creator>Ha, Jeslin Chian Hung</creator><creator>Khoo, Lay Poh</creator><creator>Ai, Le</creator><creator>Cheng, Run-Fen</creator><creator>Lim, Jing Quan</creator><creator>de Mel, Sanjay</creator><creator>Ng, Siok-Bian</creator><creator>Lim, Soon Thye</creator><creator>Cai, Qing-Qing</creator><general>Elsevier Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9356-2154</orcidid><orcidid>https://orcid.org/0000-0002-0366-5505</orcidid><orcidid>https://orcid.org/0000-0002-5755-8932</orcidid><orcidid>https://orcid.org/0000-0001-5447-3282</orcidid><orcidid>https://orcid.org/0000-0003-3732-8707</orcidid><orcidid>https://orcid.org/0000-0001-6402-4288</orcidid><orcidid>https://orcid.org/0000-0001-6051-6410</orcidid></search><sort><creationdate>20210812</creationdate><title>A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma</title><author>Tian, Xiao-Peng ; Ma, Shu-Yun ; Young, Ken H. ; Ong, Choon Kiat ; Liu, Yan-Hui ; Li, Zhi-Hua ; Zhai, Qiong-Li ; Huang, Hui-Qiang ; Lin, Tong-Yu ; Li, Zhi-Ming ; Xia, Zhong-Jun ; Zhong, Li-Ye ; Rao, Hui-Lan ; Li, Mei ; Cai, Jun ; Zhang, Yu-Chen ; Zhang, Fen ; Su, Ning ; Li, Peng-Fei ; Zhu, Feng ; Xu-Monette, Zijun Y. ; Wong, Esther Kam Yin ; Ha, Jeslin Chian Hung ; Khoo, Lay Poh ; Ai, Le ; Cheng, Run-Fen ; Lim, Jing Quan ; de Mel, Sanjay ; Ng, Siok-Bian ; Lim, Soon Thye ; Cai, Qing-Qing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-a46c238262257c592d6495e8d5a3899c82cd078f12f23873ec47f0237d7216593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tian, Xiao-Peng</creatorcontrib><creatorcontrib>Ma, Shu-Yun</creatorcontrib><creatorcontrib>Young, Ken H.</creatorcontrib><creatorcontrib>Ong, Choon Kiat</creatorcontrib><creatorcontrib>Liu, Yan-Hui</creatorcontrib><creatorcontrib>Li, Zhi-Hua</creatorcontrib><creatorcontrib>Zhai, Qiong-Li</creatorcontrib><creatorcontrib>Huang, Hui-Qiang</creatorcontrib><creatorcontrib>Lin, Tong-Yu</creatorcontrib><creatorcontrib>Li, Zhi-Ming</creatorcontrib><creatorcontrib>Xia, Zhong-Jun</creatorcontrib><creatorcontrib>Zhong, Li-Ye</creatorcontrib><creatorcontrib>Rao, Hui-Lan</creatorcontrib><creatorcontrib>Li, Mei</creatorcontrib><creatorcontrib>Cai, Jun</creatorcontrib><creatorcontrib>Zhang, Yu-Chen</creatorcontrib><creatorcontrib>Zhang, Fen</creatorcontrib><creatorcontrib>Su, Ning</creatorcontrib><creatorcontrib>Li, Peng-Fei</creatorcontrib><creatorcontrib>Zhu, Feng</creatorcontrib><creatorcontrib>Xu-Monette, Zijun Y.</creatorcontrib><creatorcontrib>Wong, Esther Kam Yin</creatorcontrib><creatorcontrib>Ha, Jeslin Chian Hung</creatorcontrib><creatorcontrib>Khoo, Lay Poh</creatorcontrib><creatorcontrib>Ai, Le</creatorcontrib><creatorcontrib>Cheng, Run-Fen</creatorcontrib><creatorcontrib>Lim, Jing Quan</creatorcontrib><creatorcontrib>de Mel, Sanjay</creatorcontrib><creatorcontrib>Ng, Siok-Bian</creatorcontrib><creatorcontrib>Lim, Soon Thye</creatorcontrib><creatorcontrib>Cai, Qing-Qing</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Blood</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tian, Xiao-Peng</au><au>Ma, Shu-Yun</au><au>Young, Ken H.</au><au>Ong, Choon Kiat</au><au>Liu, Yan-Hui</au><au>Li, Zhi-Hua</au><au>Zhai, Qiong-Li</au><au>Huang, Hui-Qiang</au><au>Lin, Tong-Yu</au><au>Li, Zhi-Ming</au><au>Xia, Zhong-Jun</au><au>Zhong, Li-Ye</au><au>Rao, Hui-Lan</au><au>Li, Mei</au><au>Cai, Jun</au><au>Zhang, Yu-Chen</au><au>Zhang, Fen</au><au>Su, Ning</au><au>Li, Peng-Fei</au><au>Zhu, Feng</au><au>Xu-Monette, Zijun Y.</au><au>Wong, Esther Kam Yin</au><au>Ha, Jeslin Chian Hung</au><au>Khoo, Lay Poh</au><au>Ai, Le</au><au>Cheng, Run-Fen</au><au>Lim, Jing Quan</au><au>de Mel, Sanjay</au><au>Ng, Siok-Bian</au><au>Lim, Soon Thye</au><au>Cai, Qing-Qing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma</atitle><jtitle>Blood</jtitle><addtitle>Blood</addtitle><date>2021-08-12</date><risdate>2021</risdate><volume>138</volume><issue>6</issue><spage>452</spage><epage>463</epage><pages>452-463</pages><issn>0006-4971</issn><eissn>1528-0020</eissn><abstract>Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing nonanthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision making. Data from 722 patients with ENKTL from international centers were analyzed. A 7-SNP–based classifier was constructed using LASSO Cox regression in the training cohort (n = 336) and further validated in the internal testing cohort (n = 144) and in 2 external validation cohorts (n = 142 and n = 100). The 7-SNP–based classifier showed good prognostic predictive efficacy in the training cohort and the 3 validation cohorts. Patients with high- and low-risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all P < .001). The 7-SNP–based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. Application of the 7-SNP–based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significantly improved PFS and OS vs radiotherapy alone in high-risk Ann Arbor stage I patients, whereas there was no statistical difference between the 2 therapeutic modalities among low-risk patients. A nomogram was constructed comprising the classifier and clinicopathological variables; it showed remarkably better predictive accuracy than either variable alone. The 7-SNP–based classifier is a complement to existing risk-stratification systems in ENKTL, which could have significant implications for clinical decision making for patients with ENKTL.
•The 7-SNP-based classifier is an effective and reliable predictor of survival for patients with ENKTL.•The 7-SNP-based signature can be used as a supplement to current risk indicators, aiding clinical decision making.
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title | A composite single-nucleotide polymorphism prediction signature for extranodal natural killer/T-cell lymphoma |
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